Metrics for Analyzing Variability and Its Implementation in Software Product Lines: A Systematic Literature Review

Abstract

This summary refers to the paper Metrics for analyzing variability and its implementation in software product lines: A systematic literature review [EYS19]. The paper was online first in 2018 and was finally published 2019 in the Information and Software Technology (IST) journal. The use of metrics for assessing software products and their qualities is well established in traditional software engineering. However, such traditional metrics are typically not applicable to Software Product Line (SPL) engineering as they do not address variability management, a key part of product line engineering. Over time, various specialized product line metrics for SPLs have been described in literature, but no systematic description of these metrics and their characteristics is currently available. This paper presents a systematic literature review, where we identify metrics explicitly designed for variability models, code artifacts, and metrics taking both kinds of artifacts into account. This captures the core of variability management for product lines. We discovered 42 relevant papers reporting 147 metrics intended to measure various aspects of variability models or code artifacts. We provide a categorization of these metrics and discuss problematic issues regarding the definition of the metrics. We also systematically assess the evaluation status of the metrics showing a current lack of high-quality evaluation in the field. Researchers and practitioners can benefit from the published catalog of variability-aware metrics and the assessment of their evaluation status.